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| Participants' Hit performance as a function of delay. (A) The relative magnification of total Hits in comparison to the individual baseline (no-target condition). (B) The same indices are calculated, respectively, for msA, B, C, and D. Error bars indicate ± 1 SE. *p<0.05 in ANOVA.
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Recent neurotechnology has developed various methods for neurofeedback (NF), in which participants observe their own neural activity to be regulated in an ideal direction. EEG-microstates (EEGms) are spatially featured states that can be regulated through NF training, given that they have recently been indicated as biomarkers for some disorders. Th...
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... further examine the effect of delay on participants' Hit performance, the raw scores were individually standardized based on the baseline period (no-target condition, see Figure 5A) because raw Hits by default have individual differences and also depend on the system threshold (r thr = 0.8, 0.75, or 0.7) that were not strictly determined individually in the current study. Figure 7 indicates the relative Hits score, the relative magnification in comparison to the individual notarget condition without delay, as a function of the inserted delay. Our results clearly suggest that the real-time effect was observed only under the no-delay condition in the total score ( Figure 7A). ...
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... 7 indicates the relative Hits score, the relative magnification in comparison to the individual notarget condition without delay, as a function of the inserted delay. Our results clearly suggest that the real-time effect was observed only under the no-delay condition in the total score ( Figure 7A). The relative Hits significantly increased from the 1-or 20-s delay conditions. ...
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... the two-way ANOVA (4-target within conditions × 3-delay within condition) revealed that the main effect of the target was significant [F(3,51) = 3.94, p = 0.0128], while that of delay and interactions were not [F(2,34) = 1.05, p = 0.3601, and F(6,102) = 1.04, p = 0.4032, respectively]. The relative Hit for msD was significantly increased from msA, B, and D, regardless of the delay, according to a multiple comparisons using Ryan's method (ps < 0.05), suggesting a potential difference in the functionality of msABCD in terms of the responsiveness of our NF system with the inserted delay ( Figure 7B). ...
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... example, BF 10 = 1.52 for total score without delay, indicates that the data are approximately 1.5 times more likely to occur under H1 than under H0, suggesting at least weak evidence in favor of H1 (a Bayes factor between 1 and 3 is considered weak evidence, but this range might be common in behavioral sciences). A confirmatory non-parametric t-test with Wilcoxon signed-rank suggested the same results, where the five conditions with black-framed bars in Figure 7 were significantly different from the baseline (ps < 0.05). ...
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... the definition of the baseline might change the results, the "task-general" baseline was also used for comparison with target conditions (Figure 8A, right). Figure 8 shows the target specificity analyzed with two possible baselines: the no-target period ("task-ready") under the no-delay condition (similar to Figure 7) and the session average (the column means for "task-general") for each delay condition (see Figure 8A, right). According to Figures 9A,B, the values are generally reduced with a delay regardless of being a Hit or Miss. ...
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... the current study, we developed a new EEGms-NF system and validated it by examining the decline in participants' performance as a function of delay. Although participants were presumably totally naive about the inserted delay as the result of the agency questionnaire also implies (Figure 6A), the real-time NF successfully increased their Hit performance in total (Figure 7A), even within a single-day experiment. This suggests that by using our NF system, participants could implicitly learn through a supervised manner how to control their own neural state, spatially represented in EEG channels, immediately during each no-delay session. ...
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... msC or msD is a candidate biomarker for some diseases (for example, schizophrenia), our system is clinically applicable for future studies as it is (without the inserted delay, of course). Although msA and msB appear more difficult to control according to the current results, they are still useful for examining the effect of long-term training, since a nonsignificant tendency for increasing was observed (Figures 7, 9). Another possible future approach would be to manipulate a parameter of threshold (spatial correlation r) individually, as well as msABCD, respectively. ...
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Dysconnectivity between cortical networks is a core feature of major depressive disorder (MDD). Electroencephalography (EEG) derived microstates are a cost effective and time sensitive method of examining the dynamics of large-scale brain networks. Previous studies examining the four traditional microstate classes of A, B, C, and D in MDD have used...
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... Other EFFECTS OF ONE SESSION OF THETA OR HIGH ALPHA NEUROFEEDBACK 31 studies have applied micro-state analysis, which identifies short, stable, distinct patterns of electrical activity measured by EEG across the scalp (Férat et al., 2022;Khanna et al., 2015;Michel & Koenig, 2018), representing various cognitive processes (Tarailis et al., 2024). Currently, few studies have attempted to modulate these neural states via neurofeedback (Asai et al., 2022;Diaz Hernandez et al., 2016), and it is necessary to assess larger samples in well-controlled protocols to highlight the potential of these methods compared to the use of conventional brain frequencies. ...
Neurofeedback techniques provide participants immediate feedback on neuronal signals, enabling them to modulate their brain activity. This technique holds promise to unveil brain–behavior relationship and offers opportunities for neuroenhancement. Establishing causal relationships between modulated brain activity and behavioral improvements requires rigorous experimental designs, including appropriate control groups and large samples. Our primary objective was to examine whether a single neurofeedback session, designed to enhance working memory through the modulation of theta or high-alpha frequencies, elicits specific changes in electrophysiological and cognitive outcomes. Additionally, we explored predictors of successful neuromodulation. A total of 101 healthy adults were assigned to groups trained to increase frontal theta, parietal high alpha, or random frequencies (active control group). We measured resting-state EEG, working memory performance, and self-reported psychological states before and after one neurofeedback session. Although our analyses revealed improvements in electrophysiological and behavioral outcomes, these gains were not specific to the experimental groups. An increase in the frequency targeted by the training has been observed for the theta and high alpha groups, but training designed to increase randomly selected frequencies appears to induce more generalized neuromodulation compared with targeting a specific frequency. Among all the predictors of neuromodulation examined, resting theta and high alpha amplitudes predicted specifically the increase of those frequencies during the training. These results highlight the challenge of integrating a control group based on enhancing randomly selected frequency bands and suggest potential avenues for optimizing interventions (e.g., by including a control group trained in both up- and down-regulation).
... Finally, EEG microstates might not only be useful for understanding our socio-affective mind, but also for modulating it. Preliminary evidence indicates that microstate-neurofeedback training is feasible in healthy participants (Diaz Hernandez et al. 2016;Asai et al. 2022). One could thus experimentally alter microstate features to induce specific socio-affective processes, e.g., experimentally increasing a key microstate's duration at rest to decrease trait-levels of anxiety. ...
Social interactions require both the rapid processing of multifaceted socio-affective signals (e.g., eye gaze, facial expressions, gestures) and their integration with evaluations, social knowledge, and expectations. Researchers interested in understanding complex social cognition and behavior face a “black box” problem: What are the underlying mental processes rapidly occurring between perception and action and why are there such vast individual differences? In this review, we promote electroencephalography (EEG) microstates as a powerful tool for both examining socio-affective states (e.g., processing whether someone is in need in a given situation) and identifying the sources of heterogeneity in socio-affective traits (e.g., general willingness to help others). EEG microstates are identified by analyzing scalp field maps (i.e., the distribution of the electrical field on the scalp) over time. This data-driven, reference-independent approach allows for identifying, timing, sequencing, and quantifying the activation of large-scale brain networks relevant to our socio-affective mind. In light of these benefits, EEG microstates should become an indispensable part of the methodological toolkit of laboratories working in the field of social and affective neuroscience.
... The resultant cluster centroids were restored to their original channel configuration (Fig. 2B, upper panel with spatial interpolation from the lower panel). Since the modified k-means was introduced to produce polarity-ignored EEGms templates (Pascual-Marqui et al., 1995), the produced maps can be reversed for polarity-assumed templates, where the frontal is red for positive templates and blue for negative templates (Asai et al., 2022). In addition to EEGms, the assembly of states as a matrix can be time-series EEG data ( Fig. 2C; for example, 500 time points). ...
The neural manifold in state space represents the mass neural dynamics of a biological system. A challenging modern approach treats the brain as a whole in terms of the interaction between the agent and the world. Therefore, we need to develop a method for this global neural workspace. The current study aimed to visualize spontaneous neural trajectories regardless of their measuring modalities (electroencephalography [EEG], functional magnetic resonance imaging [fMRI], and magnetoencephalography [MEG]). First, we examined the possible visualization of EEG manifolds. These results suggest that a spherical surface can be clearly observed within the spatial similarity space. Once valid (e.g., differentiable) and useful (e.g., low-dimensional) manifolds are obtained, the nature of the sphere, such as shape and size, becomes a possible target of interest. Because these should be practically useful, we suggest advantages of the EEG manifold (essentially continuous) or the state transition matrix (coarse-grained discrete). Finally, because our basic procedure is modality-independent, MEG and fMRI manifolds were also compared. These results strongly suggest the need to update our understanding of neural mass representations to include robust "global" dynamics.
... The microstates are also related to the data from other brain imaging modalities, such as functional Magnetic Resonance Imaging (fMRI) (Abreu et al. 2021;Britz et al. 2010;Schwab et al. 2015;Van De Ville et al. 2010), functional Near-Infrared Spectroscopy (fNIRS) (Zhang and Zhu 2019), Positron Emission Tomography (PET) (Rajkumar et al. 2021a), Transcranial Magnetic Stimulation (TMS) (Croce et al. 2018b;Qiu et al. 2020;Sverak et al. 2018), Magnetoencephalography (MEG) (Coquelet et al. 2022). The method has been successfully used in neurofeedback studies (Asai et al. 2022;Diaz Hernandez et al. 2016) and tested in rodent models (Mégevand et al. 2008;Mishra et al. 2021). ...
A growing body of clinical and cognitive neuroscience studies have adapted a broadband EEG microstate approach to evaluate the electrical activity of large-scale cortical networks. However, the functional aspects of these microstates have not yet been systematically reviewed. Here, we present an overview of the existing literature and systematize the results to provide hints on the functional role of electrical brain microstates. Studies that evaluated and manipulated the temporal properties of resting-state microstates and utilized questionnaires, task-initiated thoughts, specific tasks before or between EEG session(s), pharmacological interventions, neuromodulation approaches, or localized sources of the extracted microstates were selected. Fifty studies that met the inclusion criteria were included. A new microstate labeling system has been proposed for a comprehensible comparison between the studies, where four classical microstates are referred to as A-D, and the others are labeled by the frequency of their appearance. Microstate A was associated with both auditory and visual processing and links to subjects’ arousal/arousability. Microstate B showed associations with visual processing related to self, self-visualization, and autobiographical memory. Microstate C was related to processing personally significant information, self-reflection, and self-referential internal mentation rather than autonomic information processing. In contrast, microstate E was related to processing interoceptive and emotional information and to the salience network. Microstate D was associated with executive functioning. Microstate F is suggested to be a part of the Default Mode Network and plays a role in personally significant information processing, mental simulations, and theory of mind. Microstate G is potentially linked to the somatosensory network.
In recent years, due to the prevalence of virtual reality (VR) and human-computer interaction (HCI) research, along with the expectation that understanding the process of establishing sense of ownership, sense of agency, and limb heaviness (in this study, limb heaviness is replaced with comfort level) will contribute to the development of various medical rehabilitation, various studies have been actively conducted in these fields. Previous studies have indicated that each perceptual characteristics decrease in response to positive delay. However, it is still unclear how each perceptual characteristic changes in response to negative delay. Therefore, the purpose of this study was to deduce how changes occur in the perceptual characteristics when certain settings are manipulated using the avatar developed in this study. This study conducted experiments using an avatar system developed for this research that uses electromyography as the interface. Two separate experiments involved twelve participants: a preliminary experiment and a main experiment. As observed in the previous study, it was confirmed that each perceptual characteristics decreased for positive delay. In addition, the range of the preliminary experiment was insufficient for the purpose of this study, which was to confirm the perceptual characteristics for negative delay, thus confirming the validity of conducting this experiment. Meanwhile, the main experiment showed that the sense of ownership, sense of agency, and comfort level decreased gradually as delay time decreased, ( i.e. , this event is prior to action with intention, which could not be examined in the previous study). This suggests that control by the brain-machine interface is difficult to use when it is too fast. In addition, the distribution of the most strongly perceived settings in human perceptual characteristics was wider in regions with larger delays, suggesting this may lead to the evaluation of an internal model believed to exist in the human cerebellum. The avatar developed for this study may have the potential to create a new experimental paradigm for perceptual characteristics.
